3D Bone segmentation

Combining medical images and patient data

Firstly, the personalization of healthcare is an ideal area to benefit from machine learning. That is where medical artificial intelligence comes in. This is because a vast amount of data is already available to help boost the effectiveness of treatment.

AI in health

We combine images with patient data to detect diseases in an early stage, perform risk analysis to avoid complications, and help determine the right treatment. Furthermore, for pharmaceutical companies, Scyfer can help with data and image analysis in drug development.

Scyfer specializes in detection patterns in medical images in combination with patient data. As such, this creates whole new possibilities for:

Medical research.

A vast amount of data is collected in different modalities (such as X-ray, CT and (f)MRI) and detailed patient data is collected on the treatment and progress of diseases. Until now, these modalities were hard to combine in research. Scyfer can support data fusion of those modalities to support research. Scyfer actively participates in research programs with medical institutions.

Data processing.

To derive information from medical images, advanced post-processing steps are required in order to filter the right information from the data. Scyfer created a bone segmentation service in order to segment hip and femur bones in 3D CT scans. Scyfer provides deep-learning technology as a component added by device manufacturers to enhance functionality for end users.

Drug development.

Scyfer can detect patterns in data and images, and compare results of treatment to detect if something has changed or not. Scyfer can help prove the effect of treatment in pathology or other medical images.

Participation in research grants/

Scyfer is available to participate as a Small and Medium Enterprise (SME) in research grants like H2020 and other relevant grants with medical institutions.

Do you have any questions or an idea you want to discuss? Contact us.